Computer code for the prediction of nozzle admittance

A procedure which can accurately characterize injector designs for large thrust (0.5 to 1.5 million pounds), high pressure (500 to 3000 psia) LOX/hydrocarbon engines is currently under development. In this procedure, a rectangular cross-sectional combustion chamber is to be used to simulate the lower traverse frequency modes of the large scale chamber. The chamber will be sized so that the first width mode of the rectangular chamber corresponds to the first tangential mode of the full-scale chamber. Test data to be obtained from the rectangular chamber will be used to assess the full scale engine stability. This requires the development of combustion stability models for rectangular chambers. As part of the combustion stability model development, a computer code, NOAD based on existing theory was developed to calculate the nozzle admittances for both rectangular and axisymmetric nozzles. This code is detailed

CONCEPTUAL MAPPING MODEL ACROSS LANGUAGES: A TEST IN VIETNAMESE LANGUAGE

The conceptual metaphor, LOVE IS A JOURNEY, has been identified as a process of mapping based on the Conceptual Metaphor Theory (CMT) proposed by Lakoff and Johnson (1980). However, Ahrens (2002) pointed out several problems that the CMT may encounter, especially in setting parameters to be experimentally tested. Ahrens (2002) proposed the Conceptual Mapping Model (CMM) to investigate metaphor expressions by identifying three mappings between the source domain and the target domain: entities, qualities, and functions. After an analysis, the reason for these mappings, called a mapping principle, is indicated. In particular, the CMM can predict the processing of conceptual metaphors in terms of conventional and novel metaphors. This study is intended to test whether the CMM can perform well across languages through the experimental rates of acceptability and interpretability for different types of metaphors. Fifty Vietnamese native speakers were recruited. Each participant judged (on a Likert scale of 1-7) the levels of acceptability and interpretability of three conceptual metaphors in Vietnamese: LIFE IS A BOOK, HAPPINESS IS LIGHT, and LOVE IS FIRE. Each conceptual metaphor consists of six types of sentences, including (a) Literal pair to B, (b) Conventional metaphor, (c) Literal pair to D, (d) Novel metaphor that follows the mapping principle, (e) Literal pair to F, and (f) Novel metaphor that does not follow the mapping principle. The results of t-tests show that in terms of both acceptability and interpretability, conventional metaphors are ranked higher than novel metaphors. The results also indicate that novel metaphors that follow the mapping principle are rated higher than those that do not. Therefore, the mapping principle can constrain the image schemas so that any image that does not belong to the schemas can affect the processing of metaphors

Skill-biased technological change in Vietnam

Previous research has found evidence for the existence of skill-biased technological change in both the USA and Europe. However, similar studies are still limited in developing countries. There has not been any previous research that measured skill-biased technological change in Vietnam. The research question that this study aims to answer is if there is a skill-biased technological change in Vietnam. Based on data collected from the Vietnam Household Living Standards Survey from 2004 to 2014, this thesis measures the skill-biased technological change in Vietnam by measuring relative skill productivity. Relative skill productivity is calculated using the elasticity of substitution between skilled and unskilled workers, skill premium, the respective factor augmenting technology term of unskilled workers, and the respective factor augmenting technology term of skilled workers. The thesis developed a regression model for estimating wage as informed by the Mincer (1974) wage equation. The findings provided evidence that skill-biased technological change occurred in Vietnam during the period 2004 to 2008. It also provided empirical evidence of the wage gap between skilled and unskilled workers, between male and female workers, and between urban and rural areas. This thesis provides policy recommendations to improve the wage differential and the skill of the workers in Vietnam

INTERNAL GOVERNANCE MECHANISMS AND FIRM PERFORMANCE: THE CASE OF VIETNAM

Good corporate governance would contribute to the sustainable development of the economy. Better corporate governance is supposed to lead to better corporate performance and expropriation of controlling shareholders is supposed to be prevented. Studies of impacts of corporate governance on organizational performance had started since 1990s. Vietnam is a developing country with an underdeveloped financial market and week regulatory principles. Therefore, an approach of internal mechanism is supposed to be a better way to improve the quality of corporate governance than external mechanisms. Two internal governance mechanisms (IGMs) are examined in the relationship with corporate performance in this study include (1) Ownership structure and (2) Board of Directors. The results shows that largest shareholder, controlled directors and duality have negative impacts on firm performance while family ownership, board of director ownership, institutional ownership and foreign ownership have positive impacts on firm performance. The study makes theoretical and empirical contribution to the understanding for the development of an effective corporate governance framework in Vietnamese market

Automated essay assessment: an evaluation on paperrater’s reliability from practice / Nguyen Vi Thong

From a perspective of a PaperRater user, the author attempts to investigate the reliability of the program. Twenty-four freshman students and one writing teacher at Dalat University - Vietnam were recruited to serve the study. The author also served as one scorer. The scores generated by PaperRater and the two human scorers were analyzed quantitatively and qualitatively. The statistical results indicate that there is an excellent correlation between the means of scores generated by three scorers. With the aid of SPSS and certain calculation, it is shown that PaterRater has an acceptable reliability which implies that the program can somehow assist in grading students’ papers. The semi-structured interview at the qualitative stage with the teacher scorer helped point out several challenges that writing teachers might encounter when assessing students’ prompts. From her perspective, it was admitted that with the assistance of PaperRater, the burden of assessing a bunch of prompts at a short time period would be much released. However, how the program can be employed by teachers should be carefully investigated. Therefore, this study provides writing teachers with pedagogical implications on how PaperRater should be used in writing classrooms. The study is expected to shed new light on the possibility of adopting an automated evaluation instrument as a scoring assistant in large writing classrooms

Copula-based statistical modelling of synoptic-scale climate indices for quantifying and managing agricultural risks in australia

Australia is an agricultural nation characterised by one of the most naturally diverse climates in the world, which translates into significant sources of risk for agricultural production and subsequent farm revenues. Extreme climatic events have been significantly affecting large parts of Australia in recent decades, contributing to an increase in the vulnerability of crops, and leading to subsequent higher risk to a large number of agricultural producers. However, attempts at better managing climate related risks in the agricultural sector have confronted many challenges. First, crop insurance products, including classical claim-based and index-based insurance, are among the financial implements that allow exposed individuals to pool resources to spread their risk. The classical claim-based insurance indemnifies according to a claim of crop loss from the insured customer, and so can easily manage idiosyncratic risk, which is the case where the loss occurs independently.Nevertheless, the existence of systemic weather risk (covariate risk), which is the spread of extreme events over locations and times (e.g., droughts and floods), has been identified as the main reason for the failure of private insurance markets, such as the classical multi-peril crop insurance, for agricultural crops. The index-based insurance is appropriate to handle systemic but not idiosyncratic risk. The indemnity payments of the index-based insurance are triggered by a predefined threshold of an index (e.g., rainfall), which is related to such losses. Since the covariate nature of a climatic event, it sanctions the insurers to predict losses and ascertain indemnifications for a huge number of insured customers across a wide geographical area. However, basis risk, which is related to the strength of the relationship between the predefined indices used to estimate the average loss by the insured community and the actual loss of insured assets by an individual, is a major barrier that hinders uptake of the index-based insurance. Clearly, the high basis risk, which is a weak relationship between the index and loss, destroys the willingness of potential customers to purchase this insurance product. Second, the impact of multiple synoptic-scale climate mode indices (e.g., Southern Oscillation Index (SOI) and Indian Ocean Index (IOD)) on precipitation and crop yield is not identical in different spatial locations and at different times or seasons across the Australian continent since the influence of large-scale climate heterogeneous over the different regions. The occurrence, role, and amplitude of synoptic-scale climate modes contributing to the variability of seasonal crop production have shifted in recent decades. These variables generally complicate the climate and crop yield relationship that cannot be captured by traditional modelling and analysis approaches commonly found in published agronomic literature such as linear regression. In addition, the traditional linear analysis is not able to model the nonlinear and asymmetric interdependence between extreme insurance losses, which may occur in the case of systemic risk. Relying on the linear method may lead to the problem that different behaviour may be observed from joint distributions, particularly in the upper and lower regions, with the same correlation coefficient. As a result, the likelihood of extreme insurance losses can be underestimated or overestimated that lead to inaccuracies in the pricing of insurance policies. Another alternative is the use of the multivariate normal distribution, where the joint distribution is uniquely defined using the marginal distributions of variables and their correlation matrix. However, phenomena are not always normally distributed in practice. It is therefore important to develop new, scientifically verified, strategic measures to solve the challenges as mentioned above in order to support mitigating the influences of the climate-related risk in the agricultural sector. Copulas provide an advanced statistical approach to model the joint distribution of multivariate random variables. This technique allows estimating the marginal distributions of individual variables independently with their dependence structures. It is clear that the copula method is superior to the conventional linear regression since it does not require variables have to be normally distributed and their correlation can be either linear or non-linear. This doctoral thesis therefore adopts the advanced copula technique within a statistical modelling framework that aims to model: (1) The compound influence of synoptic-scale climate indices (i.e., SOI and IOD) and climate variables (i.e., precipitation) to develop a probabilistic precipitation forecasting system where the integrated role of different factors that govern precipitation dynamics are considered; (2) The compound influence of synoptic-scale climate indices on wheat yield; (3) The scholastic interdependencies of systemic weather risks where potential adaptation strategies are evaluated accordingly; and (4) The risk-reduction efficiencies of geographical diversifications in wheat farming portfolio optimisation. The study areas are Australia’s agro-ecological (i.e., wheat belt) zones where major seasonal wheat and other cereal crops are grown. The results from the first and second objectives can be used for not only forecasting purposes but also understanding the basis risk in the case of pricing climate index-based insurance products. The third and fourth objectives assess the interactions of drought events across different locations and in different seasons and feasible adaptation tools. The findings of these studies can provide useful information for decision-makers in the agricultural sector. The first study found the significant relationship between SOI, IOD, and precipitation. The results suggest that spring precipitation in Australia, except for the western part, can be probabilistically forecasted three months ahead. It is more interesting that the combination of SOI and IOD as the predictors will improve the performance of the forecast model. Similarly, the second study indicated that the largescale climate indices could provide knowledge of wheat crops up to six months in advance. However, it is noted that the influence of different climate indices varies over locations and times. Furthermore, the findings derived from the third study demonstrated the spatio-temporally stochastic dependence of the drought events. The results also prove that time diversification is potentially more effective in reducing the systemic weather risk compared to spatially diversifying strategy. Finally, the fourth objective revealed that wheat-farming portfolio could be effectively optimised through the geographical diversification. The outcomes of this study will lead to the new application of advanced statistical tools that provide a better understanding of the compound influence of synoptic-scale climatic conditions on seasonal precipitation, and therefore on wheat crops in key regions over the Australian continent. Furthermore, a comprehensive analysis of systemic weather risks performed through advanced copula-statistical models can help improve and develop novel agricultural adaptation strategies in not only the selected study region but also globally, where climate extreme events pose a serious threat to the sustainability and survival of the agricultural industry. Finally, the evaluation of the effectiveness of diversification strategies implemented in this study reveals new evidence on whether the risk pooling methods could potentially mitigate climate risks for the agricultural sector and subsequently, help farmers in prior preparation for uncertain climatic events